Open main menu
Home
Random
Recent changes
Special pages
Community portal
Preferences
About Wikipedia
Disclaimers
Incubator escapee wiki
Search
User menu
Talk
Dark mode
Contributions
Create account
Log in
Editing
Quantitative marketing research
(section)
Warning:
You are not logged in. Your IP address will be publicly visible if you make any edits. If you
log in
or
create an account
, your edits will be attributed to your username, along with other benefits.
Anti-spam check. Do
not
fill this in!
===Reliability and validity=== Research should be tested for [[reliability (psychometric)|reliability]], generalizability, and [[validity (psychometric)|validity]]. '''Generalizability''' is the ability to make inferences from a sample to the population. '''Reliability''' is the extent to which a measure will produce consistent results. * ''Test-retest reliability'' checks how similar the results are if the research is repeated under similar circumstances. Stability over repeated measures is assessed with the Pearson coefficient. * ''Alternative forms reliability'' checks how similar the results are if the research is repeated using different forms. * ''Internal consistency reliability'' checks how well the individual measures included in the research are converted into a composite measure. Internal consistency may be assessed by correlating performance on two halves of a test (split-half reliability). The value of the [[Pearson product-moment correlation coefficient]] is adjusted with the [[Spearman–Brown prediction formula]] to correspond to the correlation between two full-length tests. A commonly used measure is [[Cronbach's alpha|Cronbach's α]], which is equivalent to the mean of all possible split-half coefficients. Reliability may be improved by increasing the sample size. '''Validity''' asks whether the research measured what it intended to. * ''[[Content validity|Content validation]]'' (also called face validity) checks how well the content of the research are related to the variables to be studied; it seeks to answer whether the research questions are representative of the variables being researched. It is a demonstration that the items of a test are drawn from the domain being measured. * ''[[Criterion validity|Criterion validation]]'' checks how meaningful the research criteria are relative to other possible criteria. When the criterion is collected later the goal is to establish predictive validity. * ''[[Construct validity|Construct validation]]'' checks what underlying construct is being measured. There are three variants of construct validity: ''convergent validity'' (how well the research relates to other measures of the same construct), ''discriminant validity'' (how poorly the research relates to measures of opposing constructs), and ''[[Nomological network|nomological validity]]'' (how well the research relates to other variables as required by theory). * ''Internal validation'', used primarily in experimental research designs, checks the relation between the dependent and independent variables (i.e. Did the experimental manipulation of the independent variable actually cause the observed results?) * ''External validation'' checks whether the experimental results can be generalized. Validity implies reliability: A valid measure must be reliable. Reliability does not necessarily imply validity, however: A reliable measure does not imply that it is valid.
Edit summary
(Briefly describe your changes)
By publishing changes, you agree to the
Terms of Use
, and you irrevocably agree to release your contribution under the
CC BY-SA 4.0 License
and the
GFDL
. You agree that a hyperlink or URL is sufficient attribution under the Creative Commons license.
Cancel
Editing help
(opens in new window)